Assignment 3

Loading all package firstly

require(MRIcloudT1volumetrics)
require(ggplot2)
require(magrittr)
require(dplyr)
require(tidyr)
require(tidyverse)
require(plotly)

dat = read.table("https://raw.githubusercontent.com/bcaffo/ds4bme/master/data/classInterests.txt",header = TRUE)
a = table(dat$Year)
a=as.data.frame(a)
names(a) = c("Year", "Number")
g1 = ggplot(a,aes(x = Year, y = Number))
g1 = g1 + geom_col()
ggplotly(g1)

b = table(dat$Program)
b=as.data.frame(b)
names(b) = c("Program", "Number")
g2 = ggplot(b,aes(x = Program, y = Number))
g2 = g2 + geom_col()
ggplotly(g2)

x = table(dat$Year,dat$Program)
x = as.data.frame(x)
names(x) = c("Year", "Program", "Number")
g3 = ggplot(x, aes(x = as.factor(Program), 
                    y = Number, 
                    fill = as.factor(Year))
           )
g3 = g3 + geom_col()
ggplotly(g3)

hs = read.csv("https://raw.githubusercontent.com/jhu-advdatasci/2018/master/data/KFF/healthcare-spending.csv", header = TRUE, skip =2)
hs = hs[2:52,]
names(hs) = c("Location",1991:2014)
x = gather(hs,time,spend,2:25) %>% arrange(Location)
names(x) = c("States", "Year", "Spend")
g = ggplot(x, aes(x = as.factor(Year), 
                    y = Spend, 
                    fill = as.factor(States))
           )
g = g + geom_col() + theme(axis.text.x = element_text(angle = 90))
ggplotly(g)

SpendMean = x %>% group_by(States) %>% summarise(mean = mean(Spend))
g = ggplot(SpendMean, aes(x = States, y = mean))
g = g + geom_col() + theme(axis.text.x = element_text(angle = 90))
ggplotly(g)